Bridging Experimental and Computational Barriers in Needle-Biopsy Proteomics

Abstract

Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics has become a central analytical platform for the quantitative and qualitative characterization of proteins in complex biological systems, underpinning major advances in both life sciences and clinical research. Enabled by developments in protein ionization technologies and comprehensive sequence databases, this approach allows high-confidence identification and reproducible quantification of thousands of proteins in a single experiment. Importantly, MS-based proteomics enables the simultaneous assessment of protein abundance and a wide spectrum of post-translational modifications (PTMs), including phosphorylation and acetylation, without reliance on target-specific antibodies. Its versatility further allows application across diverse biological materials, ranging from cultured cells and fresh-frozen tissues to formalin-fixed, paraffin-embedded (FFPE) specimens. FFPE tissues represent the most extensive and accessible archive of human biological material, comprising billions of specimens stored in pathology departments and biobanks worldwide. These samples are frequently linked to long-term clinical follow-up data, positioning them as a uniquely powerful resource for retrospective and translational studies. While genomics and transcriptomics define cellular potential and metabolomics reflects downstream biochemical states, proteins constitute the principal functional layer of biological systems, acting as enzymes, structural elements, signaling mediators, and therapeutic targets. Despite this, protein-level analysis in clinical practice remains largely dependent on immunohistochemistry (IHC). Although well established, IHC is inherently limited by its dependence on highly specific antibodies, restricting analyses to predefined targets. Moreover, its relatively narrow dynamic range, sensitivity to variable and often limited sample input, and inability to resolve protein isoforms constrain its utility for comprehensive and discovery-driven investigations. Discovery-based MS proteomics, particularly through data-independent acquisition (DIA), overcomes many of these limitations by enabling unbiased, large-scale, and highly reproducible proteome profiling. However, the application of DIA-based proteomics to FFPE tissues remains far from routine. Significant challenges persist, including the absence of standardized and broadly applicable sample preparation protocols, time-intensive and technically demanding workflows, and the reliance on advanced bioinformatics tools for data analysis and interpretation. These limitations represent critical bottlenecks that hinder clinical implementation and, to date, have precluded the establishment of FDA-approved FFPE-based proteomic diagnostics in routine clinical practice.